Pre-screened and vetted.
Senior Software Engineer specializing in cloud-native microservices and large-scale backend systems
Senior AI/ML Engineer specializing in LLMs, multimodal AI, and scalable MLOps
“ML/NLP engineer with experience at NVIDIA and Cruise building production-grade AI systems across genomics/biomedical research and autonomous vehicle data. Has delivered multimodal LLM pipelines, large-scale entity resolution, and hybrid semantic search (BERT embeddings + FAISS + Elasticsearch), with measurable impact (≈40% accuracy/retrieval gains; ≈30% data consistency improvement) and strong MLOps practices (Kubernetes, CI/CD, MLflow, Prometheus/Grafana).”
Engineering Manager / Tech Lead specializing in large-scale distributed systems
“Software engineer focused on personalization and data/ML infrastructure who built a GenAI/LLM-driven carousel ranking system end-to-end, delivering a reported 6–7% order-rate lift. Also designed large-scale personalization ETL (15PB for ~100M users) and created a custom Airflow operator to integrate with Databricks under enterprise version constraints, with hands-on on-call and data-quality reliability improvements.”
Senior Backend/Infrastructure Engineer specializing in large-scale integrity and content systems
“Backend/platform engineer who built Bilibili’s "Avalon" content moderation platform from a vague CEO mandate into a company-wide service (Go, gRPC, Kafka), including on-call, metrics, transparency tools, and multi-site resiliency work. More recently at Meta, scaled a high-traffic mistake-prevention platform by introducing capacity levers (prefiltering, caching, log sampling, fanout limits) and navigating org-wide constraints, including debugging a rule-engine threading bottleneck.”
Staff/Tech Lead Software Engineer specializing in identity, data platforms, and cloud systems
“Engineering leader/player-coach who built and owned end-to-end sales-facing data products, including a 360° advertiser insights platform and a sales AI agent for natural-language access to insights. Demonstrated strong architecture and reliability chops (event-driven redesign to eliminate Hive-query throttling; batching/caching to reduce fan-out) plus incident ownership around ads attribution consistency. Also has 0→1 experience building graph-based recommendation/matching systems with explainability and tight user feedback loops.”
Executive Technology Leader (CTO) specializing in AI, Search, Cloud, and Edge computing
“Founder building an enterprise agentic AI startup who has already raised about $100K (friends & family plus self-funding). Has prior and current experience engaging VCs (including outreach to both large and small firms) and emphasizes demo-driven pitching, enterprise customer validation, and targeting billion-dollar market opportunities.”
Staff Software Engineer specializing in Healthcare IT and mobile platforms
Junior Software Engineer specializing in cloud data infrastructure and distributed systems
Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal systems
Staff Full-Stack Software Engineer specializing in distributed systems and healthcare platforms
Senior Full-Stack Python Engineer specializing in trading and FinTech platforms
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Senior Software Engineer specializing in cloud architecture and machine learning
Mid-level Python Backend Developer specializing in cloud-native microservices and AI/ML platforms
Senior Full-Stack Software Engineer specializing in FinTech payments and risk systems
Principal Software Engineering Manager specializing in cloud platforms and security
Senior Software Engineer specializing in AI for Healthcare and Enterprise SaaS
Executive Engineering Leader (VP/CTO) specializing in Blockchain, DeFi, and FinTech platforms
“CTO-focused candidate with experience at foundations evaluating startups, including reviewing technical architectures and coaching teams to refine ideas for better platform fit and synergies. Prioritizes company culture and integrity when choosing leadership roles.”
Executive AI/ML Engineering Leader specializing in cloud-native SaaS and GenAI platforms
“Engineering leader who modernized and unified a fragmented product suite at Milestone via a multi-year cloud-native roadmap, delivering an MVP in three quarters and boosting team velocity by 40% through cross-functional squads. At Prometheum, led a trust-building hybrid architecture (AWS control plane + customer-hosted data plane) using Kubernetes to ensure sensitive enterprise data never left customer networks while remaining cloud-agnostic across providers.”
Engineering Manager / Senior Backend Platform Engineer specializing in microservices and CI/CD
“Fitbit engineer who has taken multiple projects from concept to release, including architecting a new warranty-evaluation system that achieved 100% accuracy and saved the company $6M. Interested in exploring startup ideas and emphasizes mission alignment and building strong cross-functional teams.”
Senior Software Engineer specializing in scalable backend and platform systems
“Backend/data engineer with hands-on production experience across GCP (FastAPI microservices on Kubernetes) and AWS (Lambda, ECS Fargate, Glue). Has modernized legacy SAS batch systems into Python services with parallel-run parity validation, and has strong operational rigor in ETL reliability/monitoring plus proven SQL tuning impact (25s to <300ms, ~60% CPU reduction).”
Director-level Data Platform & Analytics Engineering Leader specializing in distributed systems
“Entrepreneurially minded builder focused on proving architecture concepts via minimal demo prototypes for marketing. Has hands-on experience improving an A/B experimentation framework by interviewing stakeholders, identifying system limits and bottlenecks, and defining success criteria to scale experimentation and speed up analysis.”
Mid-level Python Backend Developer specializing in cloud-native microservices and AI/ML platforms
“Backend/AI engineer who built a production GPU-backed real-time inference API at Nvidia and debugged burst-induced tail latency, cutting P95 by ~29% through dynamic batching and backpressure. Also shipped an end-to-end RAG + agentic operational diagnostics assistant with strict tool controls, evidence citation, confidence gating, and strong production guardrails, plus demonstrated hands-on Postgres optimization (900ms to 40–60ms).”